Sakriani Sakti

Pseudogen: A Tool to Automatically Generate Pseudo-Code from Source Code

2015

Understanding the behavior of source code written in an unfamiliar programming language is difficult. One way to aid understanding of difficult code is to add corresponding pseudo-code, which describes in detail the workings of the …

The Zero Resource Speech Challenge 2019: TTS Without T

2019

We present the Zero Resource Speech Challenge 2019, which proposes to build a\nspeech synthesizer without any text or phonetic labels: hence, TTS without T\n(text-to-speech without text). We provide raw audio for a target voice in …

Using Local Phrase Dependency Structure Information in Neural Sequence-to-Sequence Speech Synthesis

2021

We introduce end-to-end text-to-speech synthesis (TTS) with prosodic symbols that represent phrase components based on local syntactic dependency structures for synthesizing Japanese speech with natural prosody. We propose two TTS models: 1) one with prosodic …

NusaCrowd: Open Source Initiative for Indonesian NLP Resources

2022 · arXiv (Cornell University)

We present NusaCrowd, a collaborative initiative to collect and unify existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have brought together 137 datasets and 118 standardized data …

Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation

2015

Pseudo-code written in natural language can aid the comprehension of source code in unfamiliar programming languages. However, the great majority of source code has no corresponding pseudo-code, because pseudo-code is redundant and laborious to create. …